Summary 1.Understanding the effects of disease is critical to determining appropriate management responses, but estimating those effects in wildlife species is challenging. We used bovine tuberculosis (BTB) in the African buffalo Syncerus caffer population of Kruger National Park, South Africa, as a case study to highlight the issues associated with estimating chronic disease effects in a long-lived host. 2. We used known and radiocollared buffalo, aerial census data, and a natural gradient in pathogen prevalence to investigate if: (i) at the individual level, BTB infection reduces reproduction; (ii) BTB infection increases vulnerability to predation; and (iii) at the population level, increased BTB prevalence causes reduced population growth. 3. There was only a marginal reduction in calving success associated with BTB infection, as indexed by the probability of sighting a known adult female with or without a calf ( P = 0·065). 4. Since 1991, BTB prevalence increased from 27 to 45% in the southern region and from 4 to 28% in the central region of Kruger National Park. The prevalence in the northern regions was only 1·5% in 1998. Buffalo population growth rates, however, were neither statistically different among regions nor declining over time. 5. Lions Panthera leo did not appear to preferentially kill test-positive buffalo. The best (Akaike's Information Criterion corrected for small sample size) AIC c model with BTB as a covariate [exp( β ) = 0·49; 95% CI = (0·24-1·02)] suggested that the mortality hazard for positive individuals was no greater than for test-negative individuals. 6. Synthesis and applications . Test accuracy, time-varying disease status, and movement among populations are some of the issues that make the detection of chronic disease impacts challenging. For these reasons, the demographic impacts of bovine tuberculosis in the Kruger National Park remain undetectable despite 6 years of study on known individuals and 40 years of population counts. However, the rainfall and forage conditions during this study were relatively good and the impacts of many chronic diseases may be a non-linear function of environmental conditions such that they are only detectable in stressful periods.

Many studies of mammalian herbivores have employed remotely sensed vegetation greenness, in the form of Normalized Difference Vegetation Index (NDVI) as a proxy for forage quality. The assumption that reflected greenness represents forage quality often goes untested, and limited data exist on the relationships between remotely sensed and traditional forage nutrient indicators. We provide the first study connecting NDVI and forage nutrient indicators within a free‐ranging African herbivore ecosystem. We examined the relationships between fecal nutrient levels (nitrogen and phosphorus), forage nutrient levels, body condition, and NDVI for African buffalo (Syncerus caffer) in a South African savanna ecosystem over a 2‐year period (2001 and 2002). We used an information‐theoretic approach to rank models of fecal nitrogen (Nf) and phosphorus (Pf) as functions of geology, season, and NDVI in each year separately. For each year, the highest ranked models for Nf accounted for 61% and 65% of the observed variance, and these models included geology, season, and NDVI. The top‐ranked model for Pf in 2001, although capturing 54% of the variability, did not include NDVI. In 2002, we could not identify a top ranking model for phosphorus (i.e., all models were within 2 AICc of each other). Body condition was most highly correlated ($R_{adj}^{2} = 0.75$; P ≤ 0.001) with NDVI at a 1 month time lag and with Nf at a 3 months time lag ($R_{adj}^{2} = 0.65$; P ≤ 0.001), but was not significantly correlated with Pf. Our findings suggest that NDVI can be used to index nitrogen content of forage and is correlated with improved body condition in African buffalo. Thus, NDVI provides a useful means to assess forage quality where crude protein is a limiting resource. We found that NDVI accounted for more than a seasonal effect, and in a system where standing biomass may be high but of low quality, understanding available nutrients is useful for management. © 2012 The Wildlife Society.

Capturing, immobilizing, and fitting radiocollars are common practices in studies of large mammals, but success is based on the assumptions that captured animals are representative of the rest of the population and that the capture procedure has negligible effects. We estimated effects of chemical immobilization on mortality rates of African buffalo (Syncerus caffer) in the Kruger National Park, South Africa. We used a Cox proportional hazards approach to test for differences in mortality among age, sex, and capture classes of repeatedly captured radiocollared buffalo. Capture variables did not improve model fit and the Cox regression did not indicate increased risk of death for captured individuals up to 90 days postcapture [exp (β) = 1.07]. Estimated confidence intervals, however, span from a halving to a doubling of the mortality rate (95% CI = 0.56–2.02). Therefore, capture did not influence survival of captured individuals using data on 875 captures over a 5‐year period. Consequently, long‐term research projects on African buffalo involving immobilization, such as associated with research on bovine tuberculosis, should result in minimal capture mortality, but monitoring of possible effects should continue.

Invasive species are increasingly present in our ecosystems and pose a threat to the health of forest ecosystems. Practitioners are tasked with locating these invasive species and finding ways to mitigate their spread and impacts, often through costly field surveys. Meanwhile, researchers are developing remote sensing products to detect the changes in vegetation health and structure that are caused by invasive species, which could aid in early detection and monitoring efforts. Although both groups are working towards similar goals and field data are essential for validating RS products, these groups often work independently. In this paper, we, a group of researchers and practitioners, discuss the challenges to bridging the gap between researchers and practitioners and summarize the literature on this topic. We also draw from our experiences collaborating with each other to advance detection, monitoring, and management of the Hemlock Woolly Adelgid (Adelges tsugae; HWA), an invasive forest pest in the eastern U.S. We conclude by (1) highlighting the synergies and symbiotic mutualism of researcher–practitioner collaborations and (2) providing a framework for facilitating researcher–practitioner collaborations that advance fundamental science while maximizing the capacity of RS technologies in monitoring and management of complex drivers of forest health decline such as invasive species.

This paper describes robust and effective methods for the measurement of noise emissions from utility-scale wind farms and the analysis of the resulting data for determining compliance with noise level limits and standards. The methods call for primarily unattended monitoring of noise levels, wind speeds, and turbine operating conditions over many weeks, in some cases months, in order to capture the recurring maximum wind turbine-only noise level at a receptor (i.e., residence). This condition occurs when the nearest turbines are producing full acoustic output while noise from background sources is very low (particularly that from wind). Presented are the results of noise compliance measurement studies applying these methods conducted by Hankard Environmental, encompassing eight projects and 35 measurement locations in the Northeast, Midwest, and Plains regions of the United States (U.S.) The results of these measurements are used to assess the accuracy of the ISO 9613-2:1996 method in predicting wind turbine noise levels at residences. These results can be used by wind energy developers to accurately design projects to meet applicable limits and standards and give all parties involved in the permitting process a greater degree of confidence in predictions and greater clarity during compliance measurements.

This paper describes methods for the measurement of noise emissions from utility-scale wind farms and the analysis of the resulting data for determining compliance with noise level limits and standards. The methods call for primarily unattended monitoring of noise levels, wind speeds, and turbine operating conditions over many weeks, in some cases months, in order to capture the recurring maximum turbine-only noise level at a receptor (e.g., residence). This condition occurs when the nearest turbines are producing full acoustic output, while noise from background sources is very low (particularly that from wind). This paper will present the results of noise compliance measurement studies applying these methods conducted by Hankard Environmental, encompassing over 13 projects and over 50 measurement locations in the Northeast, Midwest, and Plains regions of the United States (U.S.) The results of these measurements are used to assess the accuracy of the ISO 9613-2:1996 method in predicting wind turbine noise levels on both an overall A-weighted and octave band basis. These results can be used by wind energy developers to accurately design projects to meet applicable limits and standards and gives all parties in the permitting process a greater degree of confidence in predictions and compliance measurement results.